Time Series Analysis with Spark
About this course
This course focuses on building scalable time series analysis solutions using Apache Spark, a critical skill for modern data-driven organizations. Learners gain a strong understanding of why time series analysis matters and how it supports forecasting, monitoring, and decision-making at scale. Through a structured, end-to-end approach, the course guides learners from understanding time series data to preparing datasets, performing exploratory analysis, and building robust models. You will develop practical skills to test, evaluate, and refine models while handling real-world data challenges. What sets this course apart is its emphasis on combining core time series concepts with distributed computing using Spark. Learners explore how theory translates into scalable, production-ready systems used in industry. This course is ideal for data professionals, engineers, and analysts looking to scale time series workflows using Spark. Prior experience with basic data analysis and some familiarity with programming concepts is recommended.
Price shown by Coursera — confirm on their site.
Enroll on CourseraYou'll be redirected to Coursera to complete enrollment.
- Listed & compared by CourseAsk
- English · All Levels
More courses like this
PL-300: Microsoft Power BI Data Analyst Practice Tests 2026
Udemy · Certificate
DP-900 MS Azure Data Fundamentals, 6 Tests - 300 Questions
Udemy · Certificate
PL-300 Microsoft Power BI Data Analyst: Practice Exam
Udemy · Certificate
AWS Certified Data Analytics Specialty (DAS-C01) en Español
Udemy · Bootcamp
More courses from Coursera
Coursera
TCP/IP and Internet
Birla Institute of Technology & Science, Pilani · MOOC / Non-credit
Coursera
Agile Project Management
University of Colorado Boulder · Master's Degree
Coursera
Conservation and Sustainable Development
University of Michigan · MOOC / Non-credit
Coursera
Extra-Galactic Astronomy
University of Cambridge · MOOC / Non-credit